We are looking for a motivated, independent post-doctoral and team-oriented researcher in AI and machine learning eager to work on the development of new methodologies and computing solutions to analyze complex, high-dimensional data. The project involves both real-world data analysis and new methods development. The key analytical challenge in this project is the development of methods to incorporate prior information into neural network models, as well as novel approaches for data integration based on multi-task learning.

Information about the research project

The announced post-doc position is part of a joint collaboration between the two largest research programs in Sweden, the Wallenberg AI, Autonomous Systems and Software Program (WASP) and the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS), with the ultimate goal of solving ground-breaking research questions across disciplines.

This position is part of a twin-post-doctoral research project “Data integration via auto-encoders with biological constraints”. The WASP post-doctoral researcher will join Rebecka Jörnsten’s group at Chalmers and work together with the DDLS post-doctoral researcher who will join Mika Gustafsson’s group at Linköping University. Rebecka Jörnsten’s research group at the Division of Applied Mathematics and Statistics comprises of 4 PhD students. This position is one of 3 post-doctoral openings in the group. The research group is focused on network modeling, data integration and regularization techniques in high-dimensional statistical modeling and neural networks. We collaborate with several research groups in cancer genomics and bioinformatics.

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